The determination of gas quantity, or volume is carried out under operating conditions (metering conditions). The result is an operational flow VB (TB, PB) as a function of temperature and pressure. This operational flow needs to be converted to standard conditions (TN = 0 ° C, pN = 1.01325 bar) in order to compare volumes and so that it can be used as an input for gas billing. Since the model for an ideal gas is only approximately valid for real gases at low pressures, a compressibility factor Z (T, p, xi) is introduced into the equation of state for ideal gases. The compressibility factor is mathematically approximated by a series expansion of the molar density (virial approach). The calculation of standard volume is thus given by equation 8. 3:

V(TN > Pn ) = TnPb Zn (3)

V(TB, Pb) TbPn Zb

The ratio of the compressibility factors is called the gas law deviation factor.

Two methods for calculating compressibility factors are given in G 486 including the supplementary sheets: The standard GERG-88 virial equation and the AGA8-DC92 equation of state. The former requires input parameters of p, T, HS, N, p, xCO2 and XH2, the latter the mole fractions. The AGA8 equation of state requires a full analysis by means of a process gas chromatograph.

10.1 Global availability of grasses and other wild plants

The grass family (gramineae or poaceae) is perhaps the most successful taxonomic group in the plant kingdom. Members of this group number about 9000 species distributed in about 635 genera and they grow in all ecosystems and agroclimatic zones. From economic and ecological standpoints, they are the most important species in the plant kingdom. The pea family (leguminosae or fabaceae) is the largest family of flowering plants and also contains a large number of species found flourishing in many ecosystems and agroclimatic zones. Both families of plants contain domesticated crops and wild plants which are being researched for their potentials as reliable sources of biofuels. These plants certainly have a significant role to play in an anticipated global scenario which is 100% dependent on bioenergy in the near future.

Thixotropic fluids are generally dispersions, which when they are at rest construct an intermolecular system of forces and turn the fluid into a solid, thus, increasing the viscosity. In order to overcome these forces and make the fluid turn into a liquid and which may flow, an external energy strong enough to break the binding forces is needed. Thus, as above a yield stress is needed. Once the structures are broken, the viscosity is reduced when stirred until it receives its lowest possible value for a constant shear rate (Schramm, 2000). In opposite to pseudoplastic and dilatant fluids, the viscosity of thixotrpic fluids is time dependent: once the stirring has ended and the fluid is at rest, the structure will be rebuilt. This will inform about the fluid possibilities of being reconstructed. Wastewater and sewage sludge can be examples of fluids with thixotropic behaviour (Seyssieq & Ferasse, 2003) as well as paints and soap.

1.3 Rheological mathematical models

There are several rheological mathematical models applied on rheograms in order to transform them to information on fluid rheological behaviour. For non-Newtonian fluids the three models presented below are mostly applied (Seyssiecq & Ferasse, 2003).

Elvia Ines Garcia-Pena, Alberto Nakauma-Gonzalez and Paola Zarate-Segura

Bioprocesses Department, Unidad Profesional Interdisciplinaria de Biotecnologia,

IPN, Mexico City, Mexico

1. Introduction

As many countries have taken advantage of the richness of crude oil, fossil fuels have become the main energy source, and human activities have become entirely dependent on petroleum products. However, this is not sustainable because of the huge environmental cost of harvesting and utilizing vast amounts of fossil fuels (Fairley, 2011). Therefore, the need for alternative fuels has become critical, especially for a new generation of advanced biofuels that can maximize petroleum (crude oil) displacement and minimize the side effects of burning fossil fuels. The primary objective is then to produce biofuels from corn stalks or other ‘cellulosic plants’ (or even from municipal garbage) and jet fuels from dedicated energy crops such as the fast-growing Camelina sativa (Fairley, 2011). The challenges are then to develop the agriculture for these plants and improve their utilization at an industrial scale. In this way, net reductions in petroleum use and greenhouse-gas emissions will be long-lasting and ethical. Bridging this gap will require continued investment, research, government regulations and development of technology. The International Energy Agency (IEA) has recommend the maximized use of farm, forestry and municipal wastes as well as increased cultivation of dedicated energy crops away from lands that provide carbon sequestration and other critical environmental services. One way to develop biofuels along an environmental friendly path is to draft a set of standards and practices that biofuels producers must comply with, either voluntarily or by mandate (Fairley, 2011).

In large cities, such as Mexico City with a population of more than 20 million, concerns about waste disposal and the use of alternative energy sources has steadily increased. This population produces a tremendous amount of solid waste, more than 12,000 tons per day. On the other hand, to provide sufficient food for this population, many markets are distributed throughout the city. The central market for food distribution in Mexico City, Central de Abasto (CEDA), is the second largest market in the world, receiving 25,000 tons of food products and producing 895 tons of organic solid waste each day (84% of the total solid waste produced is organic waste, 50% of that is from fruits and vegetables).

Fruit and vegetable waste (FVW) is produced in large quantities in markets in many large cities (Mata-Alvarez et al., 1992; Misi and Forster, 2002; Bouallagui et al., 2003; Bouallagui et al., 2005). The application of an anaerobic digestion process for simultaneous waste treatment and renewable energy production from the organic fraction of these residues could therefore be of great interest (Bouallagui et al., 2005). The high biodegradability of FVW promotes the rapid production of volatile fatty acids (VFAs), resulting in a rapid decrease in pH, which in turn could inhibit methanogenic activity (Bouallagui et al., 2003; Bouallagui et al., 2009). A strategy to avoid the acidification of the system is the addition of cosubstrates. Data obtained during the codigestion of FVW and other substrates resulted in the design of an efficient digestion process, improving methane yields through the positive synergistic effects of the mixed materials exhibiting complementary characteristics and the supply of missing nutrients from the cosubstrate (Agdag and Sponza, 2005, Habiba et al. 2009, Bouallagui et al. 2009). In a recently published study (Garcia-Pena et al., 2011), a 30- Liter anaerobic digestion reactor operated with a mixture of FVW:MR (meat residues) (75:25) had a stable CH4 production percentage of 53 ± 2 % and a sustained pH of 6.9 ± 0.5 (naturally regulated) in a co-digestion process. The adequate and sustained performance and stable CH4 production were a result of an appropriate buffering capacity and highly stable operation of the experimental system. However, the biogas produced during this anaerobic process needs to be cleaned before use by eliminating a relatively high content of other compounds as CO2 and H2S.

Biogas consists of approximately 60-70% (v/v) methane (CH4), 30-40% (v/v) carbon dioxide (CO2), 1-2% (v/v) nitrogen (N2), 1000-3000 ppmv H2S, 20-30 ppmv of VFAs and 10­30 ppmv of ammonia (NH3), depending on the organic substrate used during the anaerobic process (Angelidaki et al., 2003). Hydrogen sulfide (H2S) is one of the most commonly reported reduced sulfur compounds, and represents up to 2% (v/ v) . However, this H2S concentration can be higher when a rich protein feedstock is used. H2S elimination is thus required because it reduces the life span of combustion engines by corrosion, forms SO2 upon combustion and is a malodorous and toxic compound (Angelidaki et al., 2003, Pride, 2002). Malodorous gases include mainly H2S (around 3000 ppmv) and some volatile fatty acids (VFAs).

Reducing CO2 and H2S content will significantly improve the quality of biogas. There have been many technologies developed for the separation of CO2 from gas streams, including absorption by chemical solvents, physical absorption, cryogenic separation, membrane separation and CO2 fixation by biological or chemical methods (Abatzoglou and Boivin, 2009, Granite and O’Brien, 2005). These techniques are of significant industrial importance and are generally applied during natural gas sweetening and in the removal of CO2 from flue gases of power plants.

H2S is currently removed using chemical, physical or biological methods. The most commonly used method is chemical absorption by selective amines, such as diglycolamine, monoethanolamine and methyldiethanolamine, but also by absorption into aqueous solutions, physical absorption on solid adsorbents or conversion to low-solubility metal sulfides (Horikawa et al., 2004, Osorio and Torres, 2009). Water scrubbing systems are also frequently used because of their simplicity and low cost (Kapdi et al., 2005, Rasi et al., 2008). Their use allows the production of high quality CH4 enriched gas from biogas by chemical absorption where a packed bed column and a bubble column are normally used to provide liquid/gas contact (Krumdieck et al., 2008). However, the main drawbacks of these chemical technologies are the high energy requirement, the stability and selectivity of the chemicals used, the high cost of the chemicals and their regeneration, the negative environmental impacts from liquid wastes, the large equipment size requirements and the high equipment corrosion rate (Tippayawong and Thanompngchart, 2010, Fortuny et al., 2008).

Biological treatments are cost effective and environmentally friendly processes (Shareenfdeen et al., 2003, Ng et al., 2004, Maestre et al., 2010). Biofiltration is one of the most promising clean technologies for reducing emissions of malodorous gases and other pollutants into the atmosphere (van Groenestijn and Hesselink, 1993, van Groenestijn and Kraakman, 2005). This technology has been proven to effectively control reduced sulfur compounds in diluted gas streams (Yang et al., 1994, Smet et al., 1998, Ergas et al., 1995, Chung et al., 1996, Devinny et al., 1999; Gabriel and Deshusses, 2003, Kim and Deshusses, 2005). However, the elimination of H2S from fuel gases requires systems that can handle high loads of pollutants for extended periods of time (Maestre et al., 2010). Surprisingly, there is still a limited number of reports on the removal of high concentrations of H2S (>1000 ppmv) using biofilters, biotrickling filters and bioscrubbers. On the other hand, two processes have been effectively applied for the removal of high concentrations of H2S from biogas or fuel gas in industrial processes: the Thiopaq process (Paques, The Netherlands) and the Biopuric process (Biothane, USA). The first one is a chemical process that uses a conventional caustic scrubber and an expanded bed bioreactor for the recovery of spent caustic and elemental sulfur generation. The Biopuric process combines a chemical scrubber with a subsequent biological treatment.

Although H2S treatment for industrial processes has already been applied through the above-mentioned commercial systems, there is a need for the development of alternative and sustainable biological processes. Regarding the development of biofiltration and/or biotrickling filter systems to eliminate high H2S concentrations, Rattanapan et al., 2009, compared the elimination of 200 to 4000 ppmv of H2S in two biofiltration systems. One of the biofilters was a sulfide oxidizing bacterium immobilized on Granular Activated Carbon (GAC) (biofilter A) and the other was GAC without cell immobilization (biofilter B). The results showed that in the GAC system, the H2S was autocatalytically oxidized when it absorbed into the CAG, reaching a removal percentage of 85%. The removal was enhanced to over 98% (even at a concentration as high as 4000 ppmv) through the biological activity in biofilter A. In this last system, the maximum elimination capacity was approximately 125 gH2S/m3GAC h. In addition, Fortuny et al., 2008, reported the performance of a biotrickling filter system for treating high concentrations of H2S in simulated biogas using a single reactor. Two laboratory-scale biotrickling filters filled with different packing materials were evaluated, the inlet H2S concentration ranged from 900 to 12000 ppmv. During long-term operation, a removal percentage of 90% was determined with an extremely high H2S concentration (6000 ppmv). Maximum elimination capacities of 280 and 250 g H2S/m3 h were obtained at empty-bed residence times of 167 and 180 s, respectively. During this study, the main end products of the biological oxidation of H2S were sulfate and elemental sulfur; the final percentage of these products varied as a function of the ratio of O2/H2S supplied (v/v). At a value of 5.3, corresponding to an inlet H2S concentration of 3000, the main product was sulfate (60-70%), whereas at the higher H2S concentration of 6000 ppmv, the sulfate recovery decreased to 20-30%. Elemental sulfur production varied inversely with the O2/H2S supplied (v/v), it was low at a ratio of 5.3 and increased up to 68-78% as the ratio decreased.

In a biofiltration system, a gas stream is passed through a packed bed on which pollutant­degrading organisms are immobilized as biofilms. Biotrickling filters use the same principle, but an additional liquid phase will flow through the reactor. In both systems, the microorganisms in the biofilms transform the absorbed H2S by metabolic activity into elemental sulfur or sulfate depending on the amount of available oxygen. Oxygen is thus the key parameter that controls the level of oxidation. Sulfur production (Eq. 1) results from the partial oxidation of sulfide instead of complete oxidation to sulfate (Eq. 2) when oxygen is limited, as is shown in Equations 1 and 2 (Kennes and Veiga, 2001).

H2S + 0.5O2 ^ S0 + H2O (1)

H2S + 2O2 • SO4-2 + 2H+ (2)

As the performance of a biofiltration system depends on the microbial community present in the reactor, the determination of the microorganism and the microbial activity responsible for the behavior of the process is very important. However, there is still a lack of understanding of the structure and dynamics of microbial communities and the physiological role of the main microbial population as well as the correlation between the global performance of the system with the metabolic activities of the microorganisms involved in the process. This knowledge could allow control of the reactor behavior and the design of enhanced processes to eliminate high concentrations of H2S in the gas phase because the performance of the process depends on the robustness of the microbial communities (Maestre et al., 2010).

Some authors have characterized microbial population diversity present in different gas phase reactors by analysis of biomarkers such as phospholipid fatty acids (Webster et al., 1997), molecular techniques such as fluorescent in situ hybridization (FISH) (Moller et al., 1996), cloning and sequencing of ribosomal RNA genes (Roy et al., 2003), terminal restriction fragment length polymorphism (Maestre et al., 2009) and denaturing gradient gel electrophoresis (Borin et al., 2006). There are only a few studies in the literature that focused on determining the microbial diversity of microorganisms capable of removing reduced sulfur compounds in biofilters or gas phase bioreactors using molecular biological approaches. Ding et al., 2006, reported the changes in the microbial diversity of a biofilter­treating methanol and H2S. In this study, the biofilter’s initial microbial community had a high diversity, but after the biofiltration system was fed with H2S, the microbial diversity decreased to adapt to the low pH and use H2S as an energy source. Maestre et al., 2010 studied and described the bacterial composition of a lab-scale biotrickling filter (BTF) treating high loads of H2S using 16S rRNA gene clone libraries. The authors reported the diversity, the community structure and the changes in the microbial population on days 42 and 189 of reactor operation. The main changes in microbial diversity were observed at the beginning of the process and again when steady state operation was reached (i. e., neutral pH and at an inlet H2S concentration of 2000 ppmv). At steady state, the major sequences associated with SOB included Thiothrix spp., Thiobacillus spp., and Sulfurimonas denitrificans. Additionally, FISH analysis was used to determine the spatial distribution of sulfur — oxidizing bacteria (SOB) along the length of the reactor under pseudo-steady state operation. The aerobic species were found to be predominantly along the system, but some facultative anaerobes were also found. The anaerobic microorganisms were associated with higher H2S concentrations (inlet) with lower oxygen availability. The distribution of a microbial community was associated with changes in the dissolved oxygen (DO) concentration, and the accumulation of elemental sulfur and the pH (Maestre et al., 2010). Recently, Omri et al., 2011 studied the microbial community structure of the three layers (bottom, middle and top) of a biofilter using the polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) analysis. The results obtained showed a high microbial diversity for bacteria, with the relative diversity of the bacterial community represented by the number of peaks in the profiles. Significant differences were observed between the microbial communities of the three layers of the biofilter. The Simpsons diversity index was used to determine the microbial diversity in the system, and the results indicated that the bottom and middle layers exhibited high diversity (1/D of 13.6 and 10.8, respectively). However, the microbial distribution in the top layer (1/D=8.75) was associated with the vertical gradient of the substrate, as higher H2S concentrations near the inlet allowed the growth of sulfur-oxidizing bacteria and low pH provided a favorable environment for the oxidation of H2S. The predominant bacteria in samples of the operation were found to be Pseudomonas sp, Moraxellacea, Acinetobacter and Exiguobacterium belonging to the phyla Pseudomonadaceae, gamma-Proteobacteria and Firmicutes.

In the present chapter, the data obtained for the potential use of FVW and meat residues for methane production will be presented. The results demonstrating how a codigestion process of FVW and MR enhanced methane production by increasing the C/N ratio and controlling the natural pH in a 30L reactor will also be analyzed and discussed. At different stages of the start up of the anaerobic digestion system, methane production increased from 14 to 50% as a result of the use of a protein rich feedstock (MR). However, the H2S concentration also increased in the biogas stream under these conditions. Due to the increased H2S content, and considering that this compound does not allow for the efficient use of methane as fuel, a biofiltration system was evaluated in the elimination of H2S. The results obtained for the elimination of H2S and VFAs (average concentrations of 1500 ppmv and less than 10 ppmv, respectively) in the gas stream from an anaerobic process by a biofiltration system will then be presented. The microbial population in the biofilter when operating at steady state conditions is also presented and discussed.

The conventional anaerobic digesters operate as semi continuous, continuous or closed. The operations in semi continuous or continuous are preferable because the maximum growth rate can be obtained by controlling the effluent rate. In the closed system, a balance cannot be obtained while the concentrations of the components in the digester change with time (Karakashev & al., 2005).

The choice of the type of digester used is related to treated waste characteristics. Solid waste and sludge are mainly treated in digester with continuous flow (CSTRs), whereas soluble organic waste is treated by a use of biofilm systems such as the anaerobic filters and fluidized bed digesters with ascending flow (UASB) Smith & al., 2005).

In the systems of biofilm the biomass is maintained in the aggregates of the biofilm/ granule where the solid retention time (SRT) is much higher than the hydraulic retention time

(HRT). The advantage is that the digester can operate with a high flow and can tolerate higher concentrations of toxic species than in (CSTR) systems. The biofilm system operates normally in a continuous mode with an (HRT) lower than 5 days. The systems can operate in a wide range of temperature and psychrophils conditions (3°C) up to the extra — thermophiles conditions (80°C). For the anaerobic treatment of soluble organic waste the systems of UASB at high rate are used.

In CSTR systems, the biomass is suspended in the main liquid and will be removed as well as the effluent so that the solid retention time (SRT) is equal to the hydraulic retention time (HRT). This makes it necessary to operate at a high hydraulic retention time (HRT) , between 10 and 20 days, to avoid the scrubbing of the methanogens which have a long time of growth.

UF whey permeate (non-deproteinized, non diluted and non-sterilized) with the average lactose concentration of 50 g L-1 from the Dairy Plant in Nowy Dwor Gdanski, Poland, was used as a fermentation substrate (Table 2).

Continuous fermentation was carried out in the laboratory-scale plant consisted of the two UASB reactors with a working volume of 5 L each (Fig. 8). These two reactors were used to enable parallel test series with and without ultrasound irradiation. The fermentation medium was pumped continuously to the bottom part of the reaction tank by means of the peristaltic pumps. The necessary mixing was achieved through the upward wastewater flow. The reactors were water-jacketed and operated at a constant temperature of 30±1 °С. The pH of mixed liquid in the reactors was controlled automatically at pH 5.1 ± 0.2 with 2 M NaOH.

The reactors were inoculated with 40% (v/ v) solid beads containing the immobilized cells which corresponded to 39.4 g cells dry weight — DW L-1 of working bioreactor volume. After adding the cell beads inoculum to the bioreactors, before starting continuous feeding, a batch fermentation was conducted for 24 h under additional gentle agitation (100 rpm). Next the reactors worked at different HRTs of 12, 24 and 36 h. At each HRT the reactor was operated till it has reached the steady-state (the steady-state conditions were evidenced when the standard deviations of the ethanol and lactose concentrations in the effluent distillate were within 3%), thus 30 days of each fermentation step (step 1 — HRT of 12 h, step 2 — HRT of 24 h, step 3 — HRT of 36 h). The fresh inoculum was added to the reactors before each fermentation step and the aged one was removed.

The ultrasound irradiation of the reactor with yeasts was made by a special ring with a transducer (Intersonic S. C. Poland) that was attached at the bottom of the reactor. The range of the frequency generator was adjustable between 20-25 kHz and the maximum power of 50 W. The experiments were carried out with the stable sonication power of 1 W L-1 and the frequency of 20 kHz.

3.2.1.3 Analytical methods

Lactose and ethanol concentrations in the effluent distillate were determined according to Standard Methods (PN-67/A-86430; PN-A-79528-3:2007). The samples were analyzed in triplicates and results were reproducible within 3% deviation.

All fermentation steps connected with different HRTs were carried out in triplicate. Significant differences between the effects obtained in the two reactors with and without ultrasound exposure were analysed using an ANOVA F-test (Statistica 7.1 software, Statsoft Inc.) A 5% probability level was applied for all the tests. If p<0.05 from an ANOVA F-test, the differences between the effects were considered to be significantly different from one another.

Marianna Makadi, Attila Tomocsik and Viktoria Orosz

Research Institute of Nyiregyhaza, RISF, CAAES, University of Debrecen,

Hungary

1. Introduction

Digestate is the by-product of methane and heat production in a biogas plant, coming from organic wastes. Depending on the biogas technology, the digestate could be a solid or a liquid material.

Digestate contains a high proportion of mineral nitrogen (N) especially in the form of ammonium which is available for plants. Moreover, it contains other macro — and microelements necessary for plant growth. Therefore the digestate can be a useful source of plant nutrients, it seems to be an effective fertilizer for crop plants. On the other hand, the organic fractions of digestate can contribute to soil organic matter (SOM) turnover, influencing the biological, chemical and physical soil characteristics as a soil amendment.

Besides these favourable effects of digestate, there are new researches to use it as solid fuel or in the process of methane production.

In their experiments, Khemkhao et al. (2011) found that DGGE patterns of bacterial diversity of the three bacterial groups, hydrolytic, acidogenic and acetogenic, persisted at all operating temperatures. However, the distribution of their members among bacteria in each group did show small changes under the different operating conditions. By the end of the operating period, the UASB with chitosan addition was found to contain a lower proportion of hydrolytic bacteria and a higher proportion of acidogenic bacteria than the control. However, the diversity of acetogenic bacteria was found to be similar in the two reactors. Sulfate-reducing bacteria were detected in the control but not in the chitosan reactor.

It is known (Bitton, 1994) that hydrolytic, acidogenic and acetogenic bacteria work together to degrade complex organic matters into acetate, CO2 and H2. Hydrolytic bacteria begin the process of degradation by breaking down complex organic molecules such as proteins, cellulose, lignin and lipids into soluble monomer molecules by extracellular enzymes, i. e., proteases, cellulases and lipases. The monomer molecules produced are amino acids, glucose, fatty acids and glycerol. These monomers are then degraded by the acidogenic (acid-forming) group of bacteria which convert them into organic acids, alcohols and ketones, acetate, CO2, and H2. The organic acids produced include acetic, propionic, formic, lactic, butyric, and succinic acids. The alcohols and ketones produced are ethanol, methanol, glycerol and acetone. In the final stage, the acetogenic bacteria (acetate and H2-producing bacteria) convert the fatty acids, alcohols and ketones into acetate, CO2 and H2.

Two different L gas target properties have been described. Because of their basic constitutions, one bio-methane mixture is conditioned with air and the other is conditioned with a combination of air and LPG.

Table 14 shows a summary of the admixtures with which a target calorific value-oriented mixture for the low calorific base gas property can be achieved.

In the case of simple air addition, particular attention should be paid to compliance with the maximum O2 volume fraction. This should not exceed 3 % vol. in dry networks according to DVGW worksheet G 260. This quantity is reached when adding pure air to the processed biogas, at an admixture of 15 vol -% of air. In the low caloric L gases (e. g. Weser Ems gas), this limit is never reached.

Furthermore, a minimum air addition may also be necessary, in order to achieve the required Wobbe Index according to DVGW worksheet G 260.

Table 15 shows the minimum air addition for the individual processing grades of methane to achieve an L gas compliant Wobbe Index of under 13.0 kWh/m3 (NTP).

For the high-caloric L gas mixtures (target properties according to Holland II L gas) the processed biogas is conditioned with air and LPG. Table 16 shows the correlating LPG-air additions, to reach the calorific value range (+ / -2%).

The gray-shaded areas show where a compliant combination of air and LPG additions is impossible. With increasing LPG additions, the necessary addition of air is limited by the maximum O2 volume fraction of 3 %. If too little LPG is added, only the lower calorific value range can be covered. The broadest coverage of the calorific value range lies in between and is marked by the wider bandwidth of air additions.

The economy of a biogas plant consists of large investments costs, some operation and maintenance costs, mostly free raw materials, e. g., animal dung, water, aquatic weeds, terrestrial plants, sewage sludge, industrial wastes, agricultural wastes and income from sale of biogas or electricity and heat (Amigun and von Blottnitz, 2007). The economics of biogas production and consumption is dependent on a number of factors specific to the local situation, as shown in Table 4. The economics of biogas production and use, therefore, depends upon the specific country and project situation

a. Cost of biomass material, which varies among countries depending on land availability, agricultural productivity, labour costs, etc

b. Biogas production costs, which depends on the plant location, size and technology, which vary among countries

c. The cost of corresponding fossil fuel (gasoline, diesel) in individual countries

d. The strategic benefit of substituting imported petroleum with domestic resources____

Table 4. Economic factors which affect biogas production and commercialisation

The main limitations to the adoption of large-scale biogas technology are both institutional and economic. Establishing a self-sustaining institutional system that can collect and process urban waste and effectively market the generated biogas fuel is a complex activity that calls for sophisticated organisational capability and initiative (Karekezi, 1994b). The energy transition in Africa is an incremental process and not a leapfrog process, dependent upon household, national and regional accumulations of technological capabilities. Biogas technology absorption, therefore, cannot occur without the proper social, cultural, political and economic institutions to support adoption, dissemination and appropriate contextual innovation (Murphy, 2001). The Taka Gas Project in Tanzania (Mbuligwe and Kassenga, 2004) is a very good example of how large-scale biogas technology projects have failed to take off in Africa. The main objective of the Taka Gas Project was to obtain biogas through anaerobic digestion of municipal solid waste from Dar es Salaam city and serve as a model for other urban areas in Africa to emulate. The project was well prepared with analysis of solid waste as feedstock for the project, strategies for operationalising the project, environmental impacts and economic feasibility and other technical and non-technical and socio-economic issues studied for the project but it has never took off the ground due to bureaucracy.

The investment cost of even the smallest of the biogas units is prohibitive for most rural households of sub-Saharan Africa. Evidence from the experiences in Eastern and Southern African countries is still limited, but the general consensus is that the larger combined septic tank/biogas units that are run by institutions such as hospitals and schools have proved to be more viable than the small-scale household bio-digesters. There is need for subsidy-led programmes which will be demand-driven and market-oriented to increase the adoption of biogas plants. Subsidies are justified to make up for the difference between ability to pay and the higher societal benefits (maintenance of forest cover, prevention of land degradation, and reduction in emissions of greenhouse gases) and private benefits (reduction in expenditure for firewood and kerosene, savings in time for cooking and firewood collection and health) accruing to users. Besides the expense, many consumers are hesitant to adopt the biogas technology reflecting the lack of public awareness of the relevant issues. To date, this combination of factors has largely stifled the use of biogas technology in Africa.